Adaptive Robust Dynamic Balance and Motion Controls of Mobile Wheeled Inverted Pendulums

Adaptive robust dynamic balance and motion control are considered for mobile wheeled inverted pendulums, in the presence of parametric and functional uncertainties. Based on Lyapunov synthesis, the proposed control mechanisms using physical properties of wheeled inverted pendulums ensure that the outputs of the system track the given bounded reference signals within a small neighborhood of zero and guarantees semi-global uniform boundedness of all of the closed-loop signals. Simulation results are presented to verify the effectiveness of the proposed adaptive robust control.

[1]  Keng Peng Tee,et al.  Adaptive Neural Network Control of Helicopters with Unknown Dynamics , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[2]  Tao Zhang,et al.  Stable Adaptive Neural Network Control , 2001, The Springer International Series on Asian Studies in Computer and Information Science.

[3]  Jorge Angeles,et al.  The control of semi-autonomous two-wheeled robots undergoing large payload-variations , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  Nicholas R. Gans,et al.  Visual Servo Velocity and Pose Control of a Wheeled Inverted Pendulum through Partial-Feedback Linearization , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Shuzhi Sam Ge,et al.  Adaptive robust stabilization of dynamic nonholonomic chained systems , 2001, J. Field Robotics.

[6]  Alberto Isidori,et al.  Robust Autonomous Guidance: An Internal Model Approach , 2003 .

[7]  Yoon Keun Kwak,et al.  Dynamic Analysis of a Nonholonomic Two-Wheeled Inverted Pendulum Robot , 2005, J. Intell. Robotic Syst..

[8]  Jorge Angeles,et al.  On the nonlinear controllability of a quasiholonomic mobile robot , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[9]  Shin'ichi Yuta,et al.  Trajectory tracking control for navigation of the inverse pendulum type self-contained mobile robot , 1996, Robotics Auton. Syst..

[10]  Rodney A. Brooks,et al.  Sensing and Manipulating Built-for-Human Environments , 2004, Int. J. Humanoid Robotics.

[11]  Hiroshi Ishiguro,et al.  Human-like natural behavior generation based on involuntary motions for humanoid robots , 2004, Robotics Auton. Syst..

[12]  Tao Zhang,et al.  A direct adaptive controller for dynamic systems with a class of nonlinear parameterizations , 1999, Autom..

[13]  Wolfgang Hahn,et al.  Stability of Motion , 1967 .

[14]  Kaustubh Pathak,et al.  Velocity and position control of a wheeled inverted pendulum by partial feedback linearization , 2005, IEEE Transactions on Robotics.

[15]  Alfred C. Rufer,et al.  JOE: a mobile, inverted pendulum , 2002, IEEE Trans. Ind. Electron..

[16]  Jin Zhang,et al.  Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback , 2003, IEEE Trans. Neural Networks.

[17]  Lorenzo Marconi,et al.  Robust Autonomous Guidance , 2003 .

[18]  A. Blankespoor,et al.  Experimental verification of the dynamic model for a quarter size self-balancing wheelchair , 2004, Proceedings of the 2004 American Control Conference.

[19]  Shuzhi Sam Ge,et al.  Robust adaptive control of uncertain force/motion constrained nonholonomic mobile manipulators , 2008, Autom..

[20]  Chun-Yi Su,et al.  Robust motion/force control of mechanical systems with classical nonholonomic constraints , 1994, IEEE Trans. Autom. Control..